Journal ArticleDOI
Energy Conscious Scheduling for Distributed Computing Systems under Different Operating Conditions
Young Choon Lee,Albert Y. Zomaya +1 more
TLDR
This work addresses the problem of scheduling precedence-constrained parallel applications on multiprocessor computer systems and presents two energy-conscious scheduling algorithms using dynamic voltage scaling (DVS) and a novel objective function and a variant from that.Abstract:
Traditionally, the primary performance goal of computer systems has focused on reducing the execution time of applications while increasing throughput. This performance goal has been mostly achieved by the development of high-density computer systems. As witnessed recently, these systems provide very powerful processing capability and capacity. They often consist of tens or hundreds of thousands of processors and other resource-hungry devices. The energy consumption of these systems has become a major concern. In this paper, we address the problem of scheduling precedence-constrained parallel applications on multiprocessor computer systems and present two energy-conscious scheduling algorithms using dynamic voltage scaling (DVS). A number of recent commodity processors are capable of DVS, which enables processors to operate at different voltage supply levels at the expense of sacrificing clock frequencies. In the context of scheduling, this multiple voltage facility implies that there is a trade-off between the quality of schedules and energy consumption. To effectively balance these two performance goals, we have devised a novel objective function and a variant from that. The main difference between the two algorithms is in their measurement of energy consumption. The extensive comparative evaluations conducted as part of this work show that the performance of our algorithms is very compelling in terms of both application completion time and energy consumption.read more
Citations
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Journal ArticleDOI
Data Center Energy Consumption Modeling: A Survey
TL;DR: An in-depth study of the existing literature on data center power modeling, covering more than 200 models, organized in a hierarchical structure with two main branches focusing on hardware-centric and software-centric power models.
Journal ArticleDOI
Multi-User Computation Partitioning for Latency Sensitive Mobile Cloud Applications
TL;DR: This paper studies, for the first time, multi-user computation partitioning problem (MCPP), which considers the partitioning of multiple users' computations together with the scheduling of offloaded computations on the cloud resources, and designs an offline heuristic algorithm, namely SearchAdjust, to solve MCPP.
Journal ArticleDOI
An Energy-Efficient Task Scheduling Algorithm in DVFS-enabled Cloud Environment
TL;DR: Based on the amount of randomly generated DAGs workflows, the experimental results show that DEWTS can reduce the total power consumption by up to 46.5 % for various parallel applications as well as balance the scheduling performance.
Journal ArticleDOI
Workflow scheduling in cloud: a survey
Fuhui Wu,Qingbo Wu,Yusong Tan +2 more
TL;DR: This paper makes a comprehensive survey of workflow scheduling in cloud environment in a problem–solution manner and conducts taxonomy and comparative review on workflow scheduling algorithms.
Journal ArticleDOI
Energy-Efficient Stochastic Task Scheduling on Heterogeneous Computing Systems
Kenli Li,Xiaoyong Tang,Keqin Li +2 more
TL;DR: This work proposes a heuristic energy-aware stochastic task scheduling algorithm called ESTS, which can achieve high scheduling performance for BoT applications with low time complexity O(n(M + logn), where n is the number of tasks and M is the total number of processor frequencies.
References
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Journal ArticleDOI
Fine-grained dynamic voltage and frequency scaling for precise energy and performance tradeoff based on the ratio of off-chip access to on-chip computation times
TL;DR: This work presents an intraprocess dynamic voltage and frequency scaling (DVFS) technique targeted toward nonreal-time applications running on an embedded system platform that relies on dynamically constructed regression models that allow the CPU to calculate the expected workload and slack time for the next time slot and adjust its Voltage and frequency in order to save energy, while meeting soft timing constraints.
Journal ArticleDOI
Genetic scheduling for parallel processor systems: comparative studies and performance issues
TL;DR: This paper investigates an alternative paradigm, based on genetic algorithms, to efficiently solve the scheduling problem without the need to apply any restricted assumptions that are problem-specific, such is the case when using heuristics.
Journal ArticleDOI
Optimal scheduling algorithm for distributed-memory machines
Sekhar Darbha,Dharma P. Agrawal +1 more
TL;DR: A Task Duplication based Scheduling (TDS) algorithm which can schedule directed acyclic graphs (DAGs) with a complexity of O(|V|/sup 2/), where |V| is the number of tasks in the DAG.
Proceedings ArticleDOI
Bounding energy consumption in large-scale MPI programs
Barry Rountree,David K. Lowenthal,Shelby Funk,Vincent W. Freeh,Bronis R. de Supinski,Martin Schulz +5 more
TL;DR: A system that determines a bound on the energy savings for an application is developed that applies to three scientific programs, two of which exhibit load imbalance---particle simulation and UMT2K.
Proceedings ArticleDOI
Minimizing Energy Consumption for Precedence-Constrained Applications Using Dynamic Voltage Scaling
Young Choon Lee,Albert Y. Zomaya +1 more
TL;DR: This paper addresses the problem of scheduling precedence-constrained parallel applications on high-performance computing systems—specifically with heterogeneous resources—accounting for both application completion time and energy consumption by adopting dynamic voltage scaling (DVS) to minimize energy consumption.